Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

ICT-AGRI agenda on digitization of agriculture


Published on

Niels Gøtke and Christopher Brewster's presentation at the eROSA Workshop “Towards Open Science in Agriculture & Food”, a side event to High Level conference on FOOD 2030, Plovdiv, Bulgaria (13/6/2018)

Published in: Data & Analytics
  • Be the first to comment

ICT-AGRI agenda on digitization of agriculture

  1. 1. ICT-AGRI agenda on digitising agriculture: what are trends in precision farming and overview of R&I activities e-ROSA, Plovdiv 13 June 2018 Niels Gøtke and Christopher Brewster Danish Agency for Science and Higher Education and TNO ( NL)
  2. 2. Future Internet Internet of Things Big Data Precision Agriculture Sustainable Intensification More for Less Smart Applications Agriculture 4.0 Cloud computing Drones Sensors Sattellites
  3. 3. ICT-AGRI ICT-AGRI 2 18 Partners 15 Countries 23 Partners 16 Countries 2009 2014 2017 Consortium overview
  4. 4. European Research Area - NETwork Information and Communication Technology and Robotics for Sustainable Agriculture ICT-AGRI-1 2009 – 2014 ICT-AGRI-2 2014 – 2018 ICT-AGRI-3 2019-
  5. 5. Strategic Research Agenda
  6. 6. Calls for transnational projects 2010 Integrated ICT and automation for sustainable agriculture (7) 2012 ICT and automation for a greener agriculture (8) 2014 Applications for smart agriculture (with SmartAgriFood) (9) 2015 Enabling Precision Farming (8) 2017 Farm Management Systems for Precision Farming Funded and managed by National Funding Agencies
  7. 7. Call 2017 Topics 1. Agricultural research on use of sensor data for decision support Rules and algorithms for the analysis of sensor data and the output of actionable recommendations 2. Development of applications for Precision Farming Import of data from sensors, rules or algorithms for analysis of data and planning of actions, export to automated machinery 3. Cases of integration of third-party applications with Farm Management Systems Concrete integration of a third-party application in a Farm Management System.
  8. 8. FUTURE: ICT-AGRI-3 ERA-NET Cofund • Proposal for “ICT-enabled agri-food systems” in H2020 SC2 Work Programme 2019 • Core challenges of the agrifood sector ▫ food and nutrition security ▫ climate change and environmental impact ▫ social, economic and environmental sustainability.
  9. 9. Outline • Trends in hardware ▫ Trend 1: More sensors and UAVs ▫ Trend 2: More robotics ▫ Trend 3: More network connectivity • Trends in software ▫ Trend 4: Big Data ▫ Trend 5: Open/FAIR data ▫ Trend 6: Apps everywhere ▫ Trend 7: farm to fork integration/standards • Trends in the ecosystem ▫ Trend 8: Explosion of start-ups ▫ Trend 9: Consolidation and market dominance 10
  10. 10. Trend 1: Sensors and UAV • Precision Agriculture has gone from using GPS (only) as a data source to many sensors: ▫ Remote sensing via satellite – Copernicus ▫ Proximal sensing on farm machinery, in the ground, on plants ▫ Growing use UAVs to complement satellite data, using hyperspectral cameras • Much more agri machinery with sensors and actuators (up to 80% of new machinery) • Major drop in prices • Challenges: Low uptake (e.g. 35% of new spreaders have precision weighing); insufficient use of data standards; difficulty of integration with FMIS 11
  11. 11. Trend 2: More robotics • Major focus of PA research is robotics: ▫ dairy primarily (e.g. ), ▫ arable crops (e.g. and ) ▫ horticulture (greenhouses) (e.g. ) • Parallel to development of autonomous cars (different challenges) • Major area for deep learning (AI) and application of Big Data methods • Most research occurring outside agrifood (e.g. proximity sensors, image processing etc.) 12
  12. 12. Trend 3: More network connectivity • Rural areas (in EC and globally) suffer poor connectivity (only 28% of rural population have broadband): network essential for PA . • Major support from EC (e.g. Rural Summit 2017) • Essential for Smart Farming/Internet of Things/Big Data scenarios • Commercial initiatives – Wide Area Networks for IoT: ▫ LoRA ▫ Sigfox ▫ … challenged by growth of 5G • Needed for long range monitoring of agricultural land, with low energy consumption 13
  13. 13. Trend 4: Big Data • Poster child in US: Climate Corp $1Bn purchased by Monsanto • In EU, major development is Copernicus Open Data ▫ Very very large data sets e.g. ERA5 climate data is 900 Tb (terrabytes) ▫ Apps already appearing e.g. evaluation of wine using soil and meteorlogical data ( • PA is a major area for Big Data with a growing flow of data from sensors e.g. integration of field map, satellite, drone, seed drilling etc. data may involve 9000 data sets/over 3Gb • Challenge: need for greater processing power 14
  14. 14. Trend 5: Open/FAIR Data • Making data Open (freely available) or FAIR (easy available/accessible) major development • Data is new oil/Data is infrastructure • Types of Open Data for PA: ▫ Satellite data (e.g. Copernicus) ▫ Soil and Plot data (e.g. ▫ Research data sets (crop models) ▫ Commercial open data (e.g. Syngenta Good Growth Plan) • Major international support: GODAN project • Challenges: Huge variability in acceptance, need to change culture, data governance rules but also type of data 15
  15. 15. Trend 6: Apps everywhere (FMIS) • Precision Agriculture dominated by software … ▫ Migration from desktop (2000s) to ▫ Smartphone and tablet • Farm Management Information Systems ▫ Integrate multiple data sources, multiple services ▫ Growing ecosystem of Software as a Service (SaaS) ▫ E.g. 365FarmNet, Trible Farm • Plenty of standalone apps too (e.g. Virtual Vet, Wunderground) • Challenges: Lack of standards for data integration/interoperability 16
  16. 16. Trend 7: Development of Data Standards/Farm to Fork • Many available data standards ▫ For agricultural research data: AGROVOC/GACS, cf. ▫ For on farm PA: ISOBUS for machinery, AgGateway for FMIS ▫ For post farm: UN/CEFACT XML, GS1 EPCIS, EFSA, • Major roadblock is lack of data standards for sensors • The promise of IoT and Big Data depends on greater uptake of data standards 17
  17. 17. Trend 8: Explosion of start-ups • As a result of: ▫ EC investment in cascading research projects (SmartAgrifood 2, FINISH etc.) ▫ Major VC start-up capital ▫ Growth of agrifood hackathons (cf. • Many data focussed start ups for all agrifood sectors including PA • Examples: (crop monitoring), (farm management), Farmeron (dairy management), Cropti, Agricolus (farm management), (Vineyard Management) …. (cf. to see activity) • Tendency to consolidation now …, plus major danger of being overwhelmed by US capital (e.g. Fameron) 18
  18. 18. E-Rosa  ICT-AGRI • How can we address the strategic objectives of the E-Rosa community in ICT-AGRI 3? • How can ICT-AGRI 3 benefit or contribute to the agrifood open science cloud? ▫ This is not just open data ▫ This is not just standards ▫ This is also business models/motivations ▫ This is also the whole ecosystem – seeing the agrifood sector as a complex integrated system.
  19. 19. More information from our website: Thank you for your attention
  20. 20. ▫ Internet Connectivity • Internet connectivity is the process that enables individuals and organizations to connect to the Internet using computer terminals, computers, and mobile devices, sometimes via computer networks. Once connected to the Internet, users can access Internet services, such as email and the World Wide Web. Internet service providers (ISPs) offer Internet access through various technologies that offer a wide range of data signaling rates (speeds). • Mobile broadband is the marketing term for wireless Internet access delivered through mobile phone towers to computers, mobile phones (called "cell phones" in North America and South Africa, and "hand phones" in Asia), and other digital devices using portable modems. Some mobile services allow more than one device to be connected to the Internet using a single cellular connection using a process called tethering. The modem may be built into laptop computers, tablets, mobile phones, and other devices, added to some devices using PC cards, USB modems, and USB sticks or dongles, or separate wireless modems can be used. • By connecting geospatial information, cloud services and agricultural machine internet connectivity is an enabler for automation in agricultural production. Bynavn, xx.xx.xxxx - Navn og efternavn - Ændres via Indsæt>Sidehov ed & Sidefod Præsentationst itel - Ændres Side 21